Most work in pyramidal or hierarchical stereo matching has primarily used the direct coarse-to-fine or hill climbing search method. However, there are two significant problems in using the hill climbing method. First, the match at the initial scale level can be wrong. Second, the binary decision at any of the finer scale levels may be wrong. The authors present a method which is essentially a best-first or cost minimization search method and which alleviates both of these problems. Results of application to real world image pairs are presented as well as a direct comparison in terms of percentage of correct matches to the traditional hill climbing method. >